Data provided by a Global Positioning System (GPS) is typically the principal navigational sensor modality used for vehicle guidance, navigation, and control. GPS, however, has several vulnerabilities owing to unintentional and deliberate interference with GPS signals. Unintentional interference includes ionosphere interference, also known as ionospheric scintillation, and radio frequency interference stemming from television broadcasts, VHF signals, cell phones, and two-way pagers, for example.
Strategies to mitigate the vulnerabilities of GPS have tended to rely primarily on archaic and/or legacy methods. Unfortunately, such navigational modalities are limited by the range of land-based transmitters, which also tend to be expensive and ill suited for remote or hazardous environments. Accordingly, there is a need for other methods of estimating position and orientation of a vehicle when GPS data is unavailable.
Inertial Measurement Units (IMUs) are also widely used for vehicle navigation and guidance. Indeed, IMUs are frequently used as a backup to GPS. A weakness of IMUs, however, is that they can drift over time, and as a result errors may be continuously added to position estimates.
Advancements in computer vision and control theory have prompted interest in image-based techniques and systems as an alternative or adjunct to GPS. One issue that has inhibited the use of image-based systems and techniques, however, is the difficulty in reconstructing inertial measurements from a projected image. Accordingly, there remains a need for a more effective and efficient mechanism for providing image-based estimations of vehicle position and orientation.